The objective of this work is to investigate the spatial and temporal dynamics of traffic congestion propagation in urban road networks. Traffic congestion is not only a local phenomenon but a network-level process that evolves over time and spreads between interconnected road segments. The thesis will examine how congestion emerges, persists, and propagates across a transportation network, with particular attention to identifying dominant propagation paths and quantifying the strength and directionality of these interactions.

The student will develop and evaluate modeling approaches to describe congestion propagation using real or simulated traffic data. Possible methodological directions include stochastic modeling, graph-based representations of road networks, and data-driven analysis techniques. The work may involve the identification of congestion states, estimation of transition probabilities between network elements, and the characterization of propagation intensity and persistence. The results are expected to contribute to a deeper understanding of congestion dynamics and provide a basis for future predictive or control-oriented traffic management approaches.